Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Griffiths, David"'
Autor:
Bachmann, Roman, Kar, Oğuzhan Fatih, Mizrahi, David, Garjani, Ali, Gao, Mingfei, Griffiths, David, Hu, Jiaming, Dehghan, Afshin, Zamir, Amir
Current multimodal and multitask foundation models like 4M or UnifiedIO show promising results, but in practice their out-of-the-box abilities to accept diverse inputs and perform diverse tasks are limited by the (usually rather small) number of moda
Externí odkaz:
http://arxiv.org/abs/2406.09406
We propose a relighting method for outdoor images. Our method mainly focuses on predicting cast shadows in arbitrary novel lighting directions from a single image while also accounting for shading and global effects such the sun light color and cloud
Externí odkaz:
http://arxiv.org/abs/2204.09341
In this paper we set out to solve the task of 6-DOF 3D object detection from 2D images, where the only supervision is a geometric representation of the objects we aim to find. In doing so, we remove the need for 6-DOF labels (i.e., position, orientat
Externí odkaz:
http://arxiv.org/abs/2012.01230
Massive semantically labeled datasets are readily available for 2D images, however, are much harder to achieve for 3D scenes. Objects in 3D repositories like ShapeNet are labeled, but regrettably only in isolation, so without context. 3D scenes can b
Externí odkaz:
http://arxiv.org/abs/2004.02693
Autor:
Griffiths, David, Boehm, Jan
With deep learning becoming a more prominent approach for automatic classification of three-dimensional point cloud data, a key bottleneck is the amount of high quality training data, especially when compared to that available for two-dimensional ima
Externí odkaz:
http://arxiv.org/abs/1907.04758
Autor:
Griffiths, David, Boehm, Jan
Over the past decade deep learning has driven progress in 2D image understanding. Despite these advancements, techniques for automatic 3D sensed data understanding, such as point clouds, is comparatively immature. However, with a range of important a
Externí odkaz:
http://arxiv.org/abs/1907.04444
Autor:
Griffiths, David, Boehm, Jan
Recent developments in the field of deep learning for 3D data have demonstrated promising potential for end-to-end learning directly from point clouds. However, many real-world point clouds contain a large class im-balance due to the natural class im
Externí odkaz:
http://arxiv.org/abs/1904.04094
Autor:
Griffiths, David J., Hnizdo, V.
Bound charge is a useful construct for calculating the electrostatic field of polarized material, and it represents a perfectly genuine accumulation of charge. But is such a material in every respect equivalent to a particular configuration of bound
Externí odkaz:
http://arxiv.org/abs/1506.02590
Autor:
Franklin, Joel, Griffiths, David J.
A particle in hyperbolic motion produces electric fields that appear to terminate in mid-air, violating Gauss's law. The resolution to this paradox has been known for sixty years, but exactly why the naive approach fails is not so clear.
Comment
Comment
Externí odkaz:
http://arxiv.org/abs/1405.7729
Autor:
Griffiths, David J., Hnizdo, V.
Publikováno v:
Am. J. Phys. 82, 251-254 (2014)
We calculate the torque on an ideal (point) dipole moving with constant velocity through uniform electric and magnetic fields.
Comment: Spurious endnotes removed; as it will appear in Am. J. Phys
Comment: Spurious endnotes removed; as it will appear in Am. J. Phys
Externí odkaz:
http://arxiv.org/abs/1308.4569